Bibliographic record
Abstract
In the 2 years before decriminalization in British Columbia, rates of drug possession incidents were decreasing by 2% per month in British Columbia and 1% per month in the rest of Canada. After decriminalization, there was decrease of 57% in drug possession incidents in British Columbia – and no significant change in the rest of Canada, according to a research letter published June 3 in JAMA. The public health data was different, however. During the first year of decriminalization, there were no significant changes in quarterly rates of stimulant or opioid deaths, or stimulant or opioid hospitalizations. Drug decriminalization is often discussed as a way to reduce drug overdoses. The researchers compared changes in outcomes between the 2 years before decriminalization and the first year of decriminalization between British Columbia and the rest of Canada. Their study evaluated changes in police‐reported drug incidents as well as hospitalizations and deaths from opioids and stimulants in the first year after decriminalization. “Drug Decriminalization in British Columbia and Changes in Drug Crime and Opioid and Stimulant Harms” is by Adrienne Gaudreault and colleagues.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".